AIGigLab MCP Server

brandos_generate_mockup

Generate blank product mockup templates or flat print designs from a text description. Choose between template or design, set aspect ratio and resolution.

Instructions

Generate a blank product mockup template or a flat print design using AI.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>",
      "type": "<type>"
    },
    "name": "brandos_generate_mockup"
  }
}

Input Schema

Name	Required	Description	Default
`type`	Yes	Whether to generate a blank TEMPLATE or flat DESIGN
`prompt`	Yes	Description of the mockup or design
`resolution`	No	Resolution quality (e.g. '2K', '4K')	2K
`aspectRatio`	No	Aspect ratio (e.g. '1:1', '16:9')	1:1
`referenceImagePath`	No	Absolute local path to an image reference

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.3.0Jul 15, 2026

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears full responsibility for revealing behavior. It states 'using AI' but omits critical details such as whether the action is destructive, authentication requirements, rate limits, or what the output represents (e.g., URL, file path).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. No extraneous words are present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite 5 parameters and no output schema, the description fails to mention what the tool returns (e.g., image URL, local file) or hint at optional parameters like resolution and aspect ratio. The agent lacks a full understanding of the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the baseline is 3. The description adds minimal extra meaning beyond the schema (e.g., mapping 'type' to 'template or design'), but it does not expand on resolution, aspect ratio, or reference image.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('generate') and resources ('blank product mockup template or flat print design'), clearly stating the tool's purpose. It distinguishes from siblings like 'brandos_generate_asset' by focusing on mockups and designs, though not explicitly differentiating.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives (e.g., 'brandos_generate_asset' or 'generate_asset'). The description does not mention any context, prerequisites, or exclusionary cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.